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EnlistedGhost/Mistral-Small-4-119B-2603-GGUF overview

<img src="https://huggingface.co/EnlistedGhost/Mistral Small 4 119B 2603 GGUF/resolve/main/resources/Introducing%20Mistral Small 4.png" alt="Example image" wid…

ggufMistralAIMistral-Small-4VisionMulti-modalMoEGGUFllama.cppOllamaQuantize119BAgenticenfrdeesptitjakoruzharfa

Runs locally from ~1.60 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Pipeline

Repository Files & Downloads

3 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
Mistral-Small-4-119B-2603-Q4_K_XL.ggufGGUFQ4_K_XL71.65 GBDownload
Mistral-Small-4-119B-2603-Q5_K_XL.ggufGGUFQ5_K_XL86.09 GBDownload
mmproj-Mistral-Small-4-119B-2603-F32.ggufGGUFF321.60 GBDownload

Model Details

Model IDEnlistedGhost/Mistral-Small-4-119B-2603-GGUF
AuthorEnlistedGhost
Pipeline
Licenseapache-2.0
Base modelmistralai/Mistral-Small-4-119B-2603
Last modified2026-07-09T12:21:01.000Z

Model README

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language:

  • en
  • fr
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  • es
  • pt
  • it
  • ja
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  • ru
  • zh
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license: apache-2.0

new_version: EnlistedGhost/Mistral-Small-4-119B-2603-GGUF

tags:

  • MistralAI
  • Mistral-Small-4
  • Vision
  • Multi-modal
  • MoE
  • GGUF
  • llama.cpp
  • Ollama
  • Quantize
  • 119B
  • Agentic

base_model:

  • mistralai/Mistral-Small-4-119B-2603

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<img src="https://huggingface.co/EnlistedGhost/Mistral-Small-4-119B-2603-GGUF/resolve/main/resources/Introducing%20Mistral-Small-4.png" alt="Example image" width="398" height="338">

Mistral-Small-4-119B-A6B | GGUF Edition

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Coversion Details (Safetensors --> GGUF)

  • Converter: Llama.cpp (Build 9888)
  • Quantizer: Llama.cpp (Build 9760)

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Info<br />___

Thank You for Viewing This Release! <br />

*Model files (GGUF) are still being uploaded.<br />

This modelcard will be updated soon!

Your understanding and patience is very much appreciated.*

  • Mistral-Small-4-119B-A6B is a huge model in physical storage size

and due to this: Uploads are taking longer than expected.*

<br /><br />

Technical Details<br />___________________<br />These quantized GGUF files found in this release are unique<br />in the sense that when initially converting

this model it was observed that there are native Float32 (F32) weights in the layers.<br />

Upon realizing this during the initial conversion;the model was then re-converted using an "F32" flag in Llama.cpp (Version 9888)

prior to being quantized.<br />

(This was done in order to snub quality loss compared to converting to BF16 or F16 conversion+quantize)

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